Beamforming Optimization for Active RIS-Aided Multiuser Communications With Hardware Impairments

TL;DR

This work tackles sum-rate optimization in active RIS-assisted multiuser MISO systems under practical hardware impairments and RIS phase noise. It introduces a fractional-programming reformulation that decouples the problem into two SOCP subproblems for BS beamforming and RIS coefficients, solved via a block-coordinate descent framework. To curb complexity, it develops MM-based low-complexity schemes that yield closed-form updates for the BS beamforming and element-wise RIS optimization, achieving substantial gains over passive RIS under the same power budget. Simulation results demonstrate the effectiveness of active RIS in mitigating multiplicative fading, while quantifying the performance loss caused by HWIs and confirming convergence and efficiency of the proposed algorithms.

Abstract

In this paper, we consider an active reconfigurable intelligent surface (RIS) to assist the multiuser downlink transmission in the presence of practical hardware impairments (HWIs), including the HWIs at the transceivers and the phase noise at the active RIS. The active RIS is deployed to amplify the incident signals to alleviate the multiplicative fading effect, which is a limitation in the conventional passive RIS-aided wireless systems. We aim to maximize the sum rate through jointly designing the transmit beamforming at the base station (BS), the amplification factors and the phase shifts at the active RIS. To tackle this challenging optimization problem effectively, we decouple it into two tractable subproblems. Subsequently, each subproblem is transformed into a second order cone programming problem. The block coordinate descent framework is applied to tackle them, where the transmit beamforming and the reflection coefficients are alternately designed. In addition, another efficient algorithm is presented to reduce the computational complexity. Specifically, by exploiting the majorization-minimization approach, each subproblem is reformulated into a tractable surrogate problem, whose closed-form solutions are obtained by Lagrange dual decomposition approach and element-wise alternating sequential optimization method. Simulation results validate the effectiveness of our developed algorithms, and reveal that the HWIs significantly limit the system performance of active RIS-empowered wireless communications. Furthermore, the active RIS noticeably boosts the sum rate under the same total power budget, compared with the passive RIS.

Figures (8)

• Figure 1: An illustration of an active RIS-assisted multiuser MISO communication system in the presence of transceiver HWIs.
• Figure 2: Simulation setup of active RIS-assisted multiuser MISO communication system.
• Figure 3: Convergence behaviour of the proposed algorithms.
• Figure 4: CPU time of the proposed algorithms.
• Figure 5: Sum rate versus the power budget $P$.